Assessing the rainfall-agriculture and rainfall-health nutrition pathways in Uganda

Transcription

1 Assessing the rainfall-agriculture and rainfall-health nutrition pathways in Uganda George Omiat, Makerere University Gerald Shively, Purdue University ANH Academy Scientific Symposium Kathmandu, Nepal, 12 July 2017 Photo Credit Goes Here Your Institution and Partner Logo

2 Acute Food Insecurity Situation Overview in Uganda 69% of Ugandan are minimally food insecure Uganda s Global Hunger Index (GHI) score is 26.4 (vs for Nepal) 25% of the population is undernourished 34% of U5s are stunted; 6% of U5s are wasted Source: IPC Global Support Unit (January 2017):

3 Spatial Distribution of Rainfall in Uganda, Ntungamo Mbarara Sembabule Rukungiri Bushenyi Kasese Kabale Kanungu Rakai Masaka Mubende Kitgum Kamwenge Kisoro Mpigi Pader Kyenjojo Gulu Nakasongola Katakwi Apac Nebbi Kibaale Hoima Kiboga Kaberamaido Lira Kampala Bundibugyo Kabarole Kayunga Jinja Mayuge Masindi Soroti Kamuli Kotido Kumi Luwero Arua Yumbe Iganga Moyo Wakiso Pallisa Bugiri Moroto Adjumani Tororo Mukono Busia Kalangala Nakapiripirit Mbale Sironko Kapchorwa Nepal = 281mm mean=455mm Key points: wide differences in averages considerable within-district variation over time Research questions: 1) Is WHZ sensitive to rainfall? 2) What are the impacts via agriculture and nutrition? ,000 1,200 Distict average rainfall in main rainfall season 2000 to District average rainfall (in mm) in the main rainfall season; 56 districts (based on classification)

4 A-N-H pathways Rainfall Agriculture Health Nutrition But rainfall isn t a policy variable. So why study it?

5 Data Child growth (WHZ) Uganda Demographic and Health Survey (UDHS) & surveys 5,037 children under age 5 Agriculture (yields) Uganda National Household Survey (UNHS) 2005/06 & 2009/10 clusters matched to DHS Rainfall Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) Gridded estimates from NASA & NOAA Monthly time scale at 5 x 5 degree spatial resolution Covers the period January 1981-December Temperature Berkeley Earth Surface Temperature project Monthly, gridded estimates Covers the period January 1999-December

6 Assembling the data for analysis P R E C I P I T A T I O N timing of agricultural production UNHS 2009/2010 DHS timing of anthropometric measurement UNHS 2005/ DHS Jan Mar May Jun Aug Dec Jan Mar Apr May Jun Oct Dec Main rainfall season Main rainfall season Previous year 2005 or 2010 Current year or

7 WHZ vs. rainfall and temperature Current Year Previous Year 0.4 WHZ Rainfall WHZ Rainfall 600 WHZ & - M J J A S O N D Month of measurement 550 Rainfall (mm) WHZ & Rainfall tends to closely track WHZ - M J J A S O N D Month of measurement 550 Rainfall (mm) WHZ & WHZ Current Year Temperature Temperature Anomaly ( C) Temperature, less so WHZ & WHZ Previous Year Temperature Temperature Anomaly ( C) M J J A S O N D Month of measurement M J J A S O N D Month of measurement

8 Rainfall s impact on agriculture? It depends! Yield (kg/ha) U5s in low-rainfall areas potentially benefit from more rainfall via positive impacts on agriculture U5s in high-rainfall areas could suffer from higher rainfall via negative impacts on agriculture Rainfall (annual average in mm) nest: (mean) Main crop yield in district District-level average yield for main crop, observed in UNHS observation years (2005/06 and 2009/10). Banana excluded.

9 WHZ & Diarrhea Rainfall Diarrheal Disease Temperature Diarrheal Disease Child Diarrheal Disease b1jkm b1jkm b1jkm Log of Current Year Rainfall Mother Diarrheal Disease Log of Current Year Rainfall (1) Negative impact of diarrhea episodes on WHZ (2) Association is stronger at higher rainfall levels Household Diarrheal Disease Log of Current Year Rainfall Cluster and District Diarrheal Disease b1jkm b1jkm b1jkm Log of Current Year Rainfall Log of Current Year Rainfall Log of Current Year Rainfall District-level average WHZ effect for diarrhea indicator, by rainfall level, controlling for covariates

10 Impact of diarrhea episodes on WHZ The estimated impact of a diarrhea episode on WHZ is largest in the highest rainfall environments District-level estimates of cluster slopes (fixed and random effects) for diarrheal disease prevalence on WHZ at different current-year rainfall levels and current-year temperature anomalies (controlling for child, mother, household, cluster, and district characteristics).

11 WHZ and Yield 0 Rainfall Main Crop Yield 0 Temperature Main Crop Yield 0 Child Main Crop Yield b2jkm 0.10 b2jkm 0.10 b2jkm The 5.0 magnitude of 7.0 agriculture s impact on 7.0 Log of Previous Year Rainfall Log of Previous Year Rainfall WHZ is greatest in the highest rainfall Mother environments. Main Crop Yield 0 0 Household Main Crop Yield Log of Previous Year Rainfall Cluster and District Main Crop Yield b2jkm 0.10 b2jkm 0.10 b2jkm Log of Previous Year Rainfall Log of Previous Year Rainfall Log of Previous Year Rainfall District-level average effect of yield on WHZ, by rainfall level, controlling for covariates

12 Putting it all together: regression results 1. Models w/health & production pathways outperform those with only health or production: both pathways are at play. 2. Contemporaneous local rainfall is significantly and positively associated with likelihood of a diarrheal episode. Results are robust to inclusion of temperature anomalies & child/mother/household covariates. 3. Recent diarrhea has a negative and significant association with WHZ, even after controlling for all household and district covariates. Controlling for child characteristics reduces the effect magnitude by roughly half. 4. The impact of yield on WHZ is positive at moderate/high levels of rainfall. 5. The health and agricultural productivity effects of rainfall are offsetting: at low rainfall, yield effects dominate (low yield=low WHZ); at high rainfall, negative health effects offset positive crop yield effects. Policy implication: target agriculture in dry areas; health in wet areas!

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